SBIR-STTR Award

Stress wave analysis of wood piles related to ultimate compressive
Award last edited on: 12/19/2014

Sponsored Program
SBIR
Awarding Agency
USDA
Total Award Amount
$245,970
Award Phase
2
Solicitation Topic Code
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Principal Investigator
Robert D Arsenault

Company Information

Aminex Company

SE 112th Avenue NE
Sheldon, WA 98063
   N/A
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Location: Single
Congr. District: 09
County: King

Phase I

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
1985
Phase I Amount
$45,970
Wood foundation piling could be utilized for capacities of 2 to 3 current design loads if the high strength piles could be readily identified by a non-destructive test method. Woodpiles would be appreciated by geo-technical and structural engineers as an economical and reliable deep foundation capable of higher design stresses if the low-strength piles were rejected. A feasibility study will determine the degree of correlation between the longitudinal stress wave propagation along the length of the untreated piles and the failure stress in compression parallel to gain of the treated wood pile tips. The non-destructive testing technique will be developed, including testing devices.

Keywords:
1. Non-destructive evaluation

Phase II

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
1986
Phase II Amount
$200,000
Wood foundation piling could be more efficiently utilized if the high-strength piles could be readily identified and the low-strength piles could be rejected by the use of a nondestructive test method. A feasibility study was performed in SBIR Phase I research using sonic stress waves. Regression models were built using variables identified from sonic stress wave spectral analysis. Low-standard errors of estimate of compression strength indicate a high feasibility of continued success with continued research. A research study expanding the data base to 400 southern pine of different species and 50 Douglas fir piles will be used to study additional regression models, build regression models, verify models and proceed to conceptual test device prototype development.